Bayesian approach for thermal diffusivity mapping from infrared images with spatially random heat pulse heating

Abstract

This paper aims at the identification of spatially-dependent thermophysical properties and is focused on the mapping of thermal diffusivity. A one-dimensional heat conduction problem is used for the comparison of ordinary least-squares, maximum a posteriori and Markov Chain Monte Carlo methods. Simulated temperature measurements are used in the inverse analysis, which is based on a nodal strategy that results on a linear estimation problem. The nodal strategy relies on the availability of temperature measurements with fine spatial resolution and high frequency, typical of nowadays infrared cameras.